Inquiry-based adaptive prediction

ABSTRACT

Predicting future utilization of a resource. The predicting future utilization of a resource may include receiving inquiries for a potential future utilization of the resource for different future points in time, recording time-based patterns of the received inquiries, recording a historic actual utilization value of the resource, and determining a future utilization of the resource using the recorded time-based patterns of the received inquiries, the recorded historic actual utilization value of the resource and a current inquiry pattern of the resource.

BACKGROUND

One or more aspects relate to predicting future utilization of aresource.

Predictive analytics and predictive forecasting are currently hot themesin the field of business intelligence or business analytics. They may beused to forecast revenue numbers or business results based on historictransaction data. However, the same technology may be used in systemsfor predictive maintenance and preventive customer service actions. Thetechnology may also be used for forecasting potential bottlenecks inrespect to computing resources, e.g., at the end of the calculationperiod when a large amount of consolidation calculations have to bemade. All of these predictive systems have in common that anextrapolation in time is performed for a resource in question based on ahistoric real use of the resource in question.

There are several disclosures related to predicting utilization of aresource.

Document US 2012/0173477 A1, which is hereby incorporated by referenceherein in its entirety, discloses systems and methods to monitordatabase system resource consumption over various time periods, inconjunction with scheduled data loading, data export and clearingoperations. The additional activities may include generating a databasesystem resource consumption map based on the monitoring, and digestingdatabase system workload throttling to accommodate predictive databasesystem resource consumption based on the resource consumption map andcurrent system loading, prior to the current database resourceconsumption reaching a predefined critical consumption level.

Another document, US 2014/0006609 A1, which is hereby incorporated byreference herein in its entirety, is proposing a method for optimizingfuture resource usage in the cloud environment including first andsecond cloud services. Each cloud service is associated with at leastone of technical and business restrictions defining a maximum capacity.

Document US 2013/0066646 A1, which is hereby incorporated by referenceherein in its entirety, discloses a system configuration and techniquesfor optimizing schedules and associated use predictions of a multipleresource planning workflow. It may be applicable to environments, suchas radiologist scheduling in a tele-radiology workflow, and may alsoprovide forecasting and the generation of customized recommendations forscheduling and other resource scenarios. The forecast may be enhancedthrough the use of historical data models and estimated future datamodels.

It may be noted that the mentioned methods and systems rely on historictransactions actually making use of the resource. This may be equivalentto predicting future revenue numbers based on historic revenue numbers.

SUMMARY

According to one aspect, a method for predicting future utilization of aresource may be provided. The method may comprise receiving inquiriesfor potential future utilization of the resource for different futurepoints in time; recording time-based patterns of the received inquiries;recording an actual historic utilization of the resource; anddetermining future utilization of the resource using the recordedtime-based patterns of the received inquiries, the recorded actualhistoric utilization value of the resource and a current inquiry patternfor the resource.

Computer program products and systems relating to one or more aspectsare also described and may be claimed herein.

Additional features and advantages are realized through the techniquesdescribed herein. Other embodiments and aspects are described in detailherein and are considered a part of the claimed aspects.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

Embodiments of the invention will now be described, by way of exampleonly, and with reference to the following drawings:

FIG. 1 shows one example of a block diagram of an embodiment ofpredicting utilization of a resource;

FIG. 2 shows one example of a block diagram of an embodiment ofcomponents involved in executing one or more aspects;

FIG. 3 shows one example of an embodiment of a prediction system; and

FIG. 4 shows an embodiment of a computing system comprising theprediction system.

DETAILED DESCRIPTION

In the context of this description, the following conventions, termsand/or expressions may be used:

The term “resource” may denote any product, e.g. a computer component,or service that may be pre-ordered, used at a later time or, which pricemay vary according to a rareness of the resource.

The term “future point in time” may denote any time in the futurecompared to an actual time inquiries regarding the resource may belaunched or a prediction may be performed.

The term “inquiry” may denote a request about information, e.g., anavailability of the resource. It may also denote the availability of theresource for a certain price. It may also denote any information requestabout the resource. An inquiry is not a reservation for the request or adefinitive booking of the request.

The term “potential future utilization” may denote an eventual usage ofthe resource. The resource may or may not be utilized by the inquirer.There may not be any relationship between the inquiry and the actualusage or utilization of the resource. The inquiry and the actual laterutilization may be decoupled completely.

The term “time-based pattern”, in particular of time-based patterns ofinquiries, may denote a development of the number of inquiries for theresource over time. It may be noted that different sets of time basedinquiry patterns may exist in parallel. One set of inquiries may bedirected towards an interest in information about the resource at afirst time in the future, and another set of inquiries may demonstratean interest in information about the resource at a second time in thefuture. Both inquiry sets may not be intermixed because the inquiriesmay be independent from each other. An inquiry for a request at onefuture point in time may be another object than a request at anotherfuture point in time.

It may be noted that recorded, i.e., historic time-based patterns may bedifferentiated from a current pattern of inquiries. The current patternof inquires may be defined as the pattern of inquires available at thepoint in time of the prediction.

The term “historic actual utilization” may denote the historic values ofthe utilization of the resource. Here, it may be noted that no parallelsets of utilization values may be required. A resource may only have oneactual utilization value—representing a utilization rate—per timeinterval in the past.

The term “time dependent service” may denote any product or service withvarying demand and varying number of orders or bookings per time unit.An inquiry for such a resource may, e.g., be visible by use of theInternet.

One or more aspects predict future utilization of the resource inquestion which is not only based on historic actual transactionsregarding the utilization of the resource. In this, a historictransaction may comprise a request for the resource and consequently afulfillment of the request. Thus, in systems and methods according tothe state-of-the-art, there is a one-to-one relationship between arequest and the fulfillment of the request for the resource.

One aspect proposed here does not only include requests and fulfillmentsof the requests, i.e., actual resource utilization for a resource. Incontrast to conventional approaches, one or more aspects consider aninterest in information about utilization of the resource, notnecessarily the resource itself.

Thus, it is not the booking on which the prediction is based but, e.g.,only the interest in a particular resource.

It may be noted that one aspect of the proposed technique is itsadaptability. No background model of the predicted resource availabilitymay be required. No assumptions need be made for any exception in thedevelopment of the availability of the resource. One or more aspectsadapt itself to changing conditions. If the prediction system or methodmay be implemented as part of a road navigation system and a road-pathmay be partially blocked by road works, the system would implicitlyconsider the reduced capacity and would reflect that in the prediction.

An example from the stock market may make this more transparent. Oneway—or a plurality of ways—of predicting a future stock trading volumeor stock price may be based on the historic development of the stockprice which may include buy-side and sell-side orders which typicallyresults—by way of supply and demand—in an actual stock price and/ortrading volume. Other parameters may be reflected in the conventionalpredictive stock price systems, like general market dynamics, adevelopment of stock prices of stocks of the same industry group, and soon.

However, all of these techniques may not reflect an abstract interest inthe stock in question. Such an abstract interest may be made concrete byobserving inquiries of the stock price over time. These inquiries may inmany cases not lead to a purchase of a number of stocks; only a verysmall number of inquiries may lead to a stock purchase. These purchasesmay then represent the basis for the conventional predictive systems.However, and in contrast to the conventional prediction systems, thepotentially far bigger number of inquiries of a stock price or tradingvolume may not be reflected in traditional prediction systems.

Thus, one or more aspects may deliver a more precise prediction offuture resource utilization. One or more aspects may provide a moreprecise prediction of future resource utilization, which may not rely onhistoric transactions, like reservations, orders and requests for theresource.

According to one embodiment, the historic actual utilization orutilization value may be recorded as an average utilization value duringdiscrete predefined time periods, in particular time periods in thepast. The discrete value of a time slot may depend on the type ofresource. A trading volume of stocks may be based in a second average;if the resource may be a sector of a motorway, the time slot foraveraging may be a couple of minutes.

According to a further embodiment, the resource may be selected to be apart of a road-path, in particular a sector of a motorway or a specificcrossing, from a first geo-position to a second geo-position. Thus, anavigation system, in which such a prediction system may be included,may plan ahead depending on the predicted usage of the sector of themotorway ahead. Thus, it may not only react to traffic messagesreflecting the current traffic situation but plan ahead for the time tocome during the journey with a vehicle.

According to one embodiment, the inquiring of potential futureutilization of the part of the road-path may be regularly performed by anavigation system. In doing so, the navigation system may generateregular plan-ahead scenarios based on the prediction of the road-pathusage. If a plurality of navigation systems in cars make the inquirieson a regular basis after a path from location A to location B has beenplanned, the prediction system may be able to foresee traffic congestionfar in advance. The traffic, in particular the drivers via theirextended navigation, may be informed in advance of a happeningcongestion. The road may have a much better utilization rate withoutcongestion.

According to another embodiment, the determining the future utilizationof the resource may also be based on a parameter reflecting externalinfluence factors of the historic actual utilization. That may, e.g., bethe hour of the day the resource is planned to be used, the day of theweek, the season, the vacation period, the weather or the weatherforecast, or any other environmental parameter that may influence theutilization or availability of the resource. Thus, an even more preciseprediction also using heuristic algorithms or a rule based systemconsidering one or more parameters that may be possible. The one or moreparameters may influence the rule.

According to another embodiment, the resource may be selected to be atrading volume of stocks. If people may observe the stock price or thetrading volume now and then using Internet platforms showing the actualtrading volume or stock price, a prediction of a future trading volumeor stock price at a given point in time in the future may be made.

According to another embodiment, the resource may be an availability ofa time dependent service. Such a service may have different appearances.It may be an availability of a flight ticket for a flight fromdestination A to destination B at a given future time frame or aspecific flight identifiable by a flight number. It may also apply forbookings for ferries, busses, concerts, theatre tickets and so on. Thepossibilities are unlimited. Any resource that may have a varyingavailability in the future and potentially a varying price, based on thedemand and/or just interest, may be a target of the inquiry basedprediction.

It may be noted that the prediction may not be performed on historictransactions like in a supply and demand system.

Furthermore, embodiments may take the form of a computer programproduct, accessible from a computer-usable or computer-readable mediumproviding program code for use, by or in connection with a computer orany instruction execution system. For the purpose of this description, acomputer-usable or computer-readable medium may be any apparatus thatmay contain means for storing, communicating, propagating ortransporting the program for use, by or in a connection with theinstruction execution system, apparatus, or device.

The medium may be an electronic, magnetic, optical, electromagnetic,infrared or a semi-conductor system for a propagation medium. Examplesof a computer-readable medium may include a semi-conductor or solidstate memory, magnetic tape, a removable computer diskette, a randomaccess memory (RAM), a read-only memory (ROM), a rigid magnetic disk andan optical disk. Current examples of optical disks include compactdisk-read only memory (CD-ROM), compact disk-read/write (CD-R/W), DVDand Blu-Ray-Disk.

It should also be noted that embodiments of the invention have beendescribed with reference to different subject-matters. In particular,some embodiments have been described with reference to method typeclaims whereas other embodiments have been described with reference toapparatus type claims. However, a person skilled in the art will gatherfrom the above and the following description that, unless otherwisenotified, in addition to any combination of features belonging to onetype of subject-matter, also any combination between features relatingto different subject-matters, e.g., between features of the method typeclaims and features of the apparatus type claims, is considered as to bedisclosed within this document.

The aspects defined above and further aspects of the present inventionare apparent from the examples of embodiments to be describedhereinafter and are explained with reference to the examples ofembodiments, but to which the invention is not limited.

In the following, a detailed description of the figures will be given.All instructions in the figures are schematic. First, a block diagram ofan embodiment of predicting future utilization of a resource is given.Afterwards, embodiments of the prediction system are explained.

FIG. 1 shows a block diagram of an embodiment of a method 100 forpredicting future utilization of a resource in a future point in time.The shown method 100 comprises receiving, 102, inquiries for a potentialfuture utilization of the resource for different future points in time.It may be noted that no fixed bookings or orders are received orrecorded—the inquiry may just express an interest in the resource.

The method, as shown, also comprises recording, 104, time-based patternsof the received inquiries. The different patterns may comprise an amountof the number of inquiries over time for utilization of the resource fordifferent given future points in time.

The method as shown also comprises recording, 106, an actual historicutilization, in particular in the form of a measurement value of theresource, and determining, 108, or calculating, based on a formula,future utilization of the resource using, for instance, the recordedtime-based patterns of the received inquiries, the recorded actualhistoric utilization values of the resource and the current inquirypattern for the resource.

FIG. 2 shows a block diagram of an embodiment 200 of components involvedin executing the method 100 for predicting future utilization of aresource. A prediction system 204 may use as input values measurementvalues of historic actual utilization values 206 of the resource.Additionally, the prediction system 204 may use the historic number ofinquiries 208, i.e., a plurality of inquiries, the inquiries forutilization of the resource at a specific time in the future and currentinquires 209 for the resource. Different inquiry patterns may exist inparallel for the same resource but for different points in time. Theutilization rates of the resource may be determined based on a timeinterval which may depend on the kind of resource.

The prediction system 204 may also be adapted to manage and store thehistoric actual utilization values 206 as well as capturing the historicnumber of inquiries 208.

The prediction system 204 may also be adapted to perform predictions ordetermine future utilization of different resources 1 . . . n inparallel, 202, 203. Consequently, different sets of historic actualutilization values 206 may be managed and stored in parallel.Furthermore, a plurality of sets of received inquiries 208 and recordedtime-based patterns of the received inquiries 209 may be managed andstored by the prediction system 204.

As output, the prediction system 204 may deliver the determined futureutilization of the resource. Different predictions may be performed fordifferent points in time in the future. Furthermore, the method may alsocomprise predicting future utilizations of a plurality of resources fordifferent points in time, as indicated by a prediction for a pluralityof resources 203.

The historic number of inquiries 208 may be captured by one or moreinquiry capturing devices 214, whereas the historic actual utilizationvalues 206 may be monitored and captured by one or more utilizationmonitor(s) 212. Furthermore, one or more additional rules 210 may beapplied as input to the prediction system, e.g., influenced byparameters.

As one model of determining future utilization of a resource, thefollowing example may be considered:

At a prediction time t_(pred), the following historic actual utilizationvalues 206 may have been recorded alongside with a number of inquiriesat different times before that historic actual utilization value 206:

TABLE 1 >30 all actual inquiry >1 >6 >2 >1 min - >15 in- utilizationpattern Day h h h num min quiries (util) current 3 45 75 99 120 Phistorical t-1 4 37 97 143 180 270 340 72% historical t-2 3 47 78 101120 250 305 48% historical t-3 2 25 53 78  90 176 203 18% historical t-41 23 38 49  60 89 105 12%

In this example, it is desired to know now (=point in time t), how theutilization of the resource (P) will be in 30 minutes from now.

The first row of the table above shows the current inquiry pattern. Upto now, 120 inquiries have been received. In this example, consider onlythe accumulated number of inquiries that have been received up to 30 minbefore the point of time at which the utilization is predicted (columnwith underlined values, >30 min). In order to predict the utilization ofthe resource in a future point in time, this example considers the 4most recent historical patterns (t-1, t-4) and the correspondingrecorded actual utilization values.

The utilization of the resource (P) may then be calculated as:P=num×sum(weight_(t-i)×(util_(t-i)/num_(t-i)), i=1 . . . 4,wherein weight_(t-i), i=1, . . . , 4; weight₁+ . . . +weight₄=1 areweights for historical data, that allows more recent data to contributemore to the calculation than older data.

Using weights of ½, ¼, ⅛, ⅛ results in:

P=120×(½×72%/180+¼×48%/120+⅛×18%/90+⅛×12%/60)=45%, the predictedutilization of the resource.

As a comparable model of determining future utilization of a resource,the following slightly adapted example may also be considered:

At a prediction time t_(pred), the following historic actual utilizationrates may have been recorded alongside with a number of inquiries fordifferent times before that historic actual utilization:

TABLE 2 at time before number of inquiries utilization of resource theprediction 180 72% −10 min. 120 48% −20 min. 90 18% −30 min. 60 12% −40min.

The table may be interpreted as follows: at a point in time t_h1 whichequals t_(pred) minus 10 minutes, i.e., 10 minutes before the currentprediction time, the utilization was 72%; and, e.g., 30 minutes beforet_h1 there have been 180 inquiries for the time t_h1. The second row maybe interpreted in a similar way, i.e., for t_h2 which equals t_(pred)minus 20 minutes; and so on.

It may be noted that for an inquiry or prediction not the actualutilization is used but the prediction is based on historical inquiresfor related historical utilizations.

Weighting factors may be used for determining a prediction of theutilization of the resource. Assume that the number of inquiries at thetime of the prediction is 120 and that a prediction shall be made ofutilization at a time 30 minutes in the future. Then, the predictedutilization may be determined using the following formula:u _(F) =W*num_(inq), whereinu_(F)=future utilization,W=weighting factor, andnum_(inq)=number of inquiries at prediction time for a fixed point intime in the future.

The weighting factor may be determined with experiments. Generally itmay be assumed that the closer the utilization rates and capturedinquiries are to the prediction time the higher the weighting may be.E.g.,

W=½*(72%/180)+¼*(48%/120)+⅛*(18%/90)+⅛*(12%/60). Please note that thenumbers used are identical to the numbers used in the previous example.However, this does not have to be the case.

The factors in front of the brackets may be determined based onexperience. The number in the brackets may easily be correlated with thevalues in table 1.

In this example a utilization rate of 45% may be determined:u _(F)=0.375*120=45%.

However, any other determination model for the prediction based on therecorded inquiry patterns and the historic actual utilization value maybe used.

In a more general form, an example of a determination algorithm for theprediction of utilization of a resource may be performed as follows:

Let n=number of records in historical data to be considered for aprediction.

Let w_(i), i=1, . . . , n where i₁+ . . . +i_(n)=1 represent weights forhistorical data (typically, lower when older).

Let B_(i), i=1, . . . , n be content of buckets stored in historicaldata.

Let U=set of possible values for utilization. For example U=(0% . . .100%) or U=(“green”, “yellow”, “red”).

Let a_(i)∈U, i=1, . . . , n be actual utilization stored in historicaldata.

Let u(x): N→U utilization function, i.e., enumeration of possiblevalues.

Let b=content of relevant bucket in the sample.

Then, the prediction may be calculated as:P=u(b×sum(w _(i)×(u ⁻¹(a _(i))/B _(i)), i=1 . . . n)).

A couple of additional comments regarding the prediction method may makethe concept more comprehensible. Since this sample of inquiries iscontinuously built from executed inquiries, the time difference δbetween the prediction time t_(pred) or T₀ and the target point in timeT for the prediction is important for the prediction calculation.Therefore, each record in the sample of inquiries and the historicalactual utilization rate also may contain δ. In order not to store everyinquiry, each record may contain multiple buckets. Each bucket mayrepresent a time range and may hold the aggregated number of inquiriesthat have been performed within this time range. Usually, the number ofinquiries per time unit increases over time, i.e., when the target pointin time T is approaching. Thus, buckets that represent the time rangecloser to T may hold a shorter interval. Examples of decreasing sampletimes may be as follows:

[>1 day], [>12 h], [>6 h], [>3 h], [>75 min.], [>30 min], [all].

For historical data, the relation between content of buckets andinformation about actually availability is evaluated. This relation isused to conclude a prediction from the content of the buckets in thesample. Historical data may not be considered anymore, if the databecomes too old. Those data may be deleted. The deletion time period maybe redefined. Thus, the amount of historical data is basically constant.

Furthermore, more recent historical data may be considered moreimportant and should influence the prediction more than older historicaldata. To do so, a factor called weight—as explained above—is used. Morerecent historical data appear with higher weights in the predictionformula.

FIG. 3 shows a block diagram of an embodiment of the prediction system204 for prediction of future utilization of a resource in a future pointin time. The prediction system 204 comprises a receiving unit 302adapted for receiving inquiries on a potential future utilization of theresource for different future points in time, a first recording unit 304adapted for recording time-based patterns of the received inquiries 208,and a second recording unit 306 adapted for recording a historic actualutilization value 206 of the resource. Furthermore, the predictionsystem 204 also comprises a determining unit 308 adapted for determininga future utilization of the resource using, for instance, the recordedtime-based patterns of the received inquiries, the recorded historicactual utilization values 206 of the resource, and the current inquirypattern for the resource.

The resource may be any service and/or product having a varying,time-based utilization and potentially a varying price for the serviceor products. This may apply to, e.g., tickets for a flight from adestination A to a destination B at a given time, theater tickets, busseat tickets, a price of a stock, trading volume of a stock, ferryutilization, utilization of an IT resource in a computing center,utilization rate of seats in a football stadium for a given match, apart of a road-path from a destination A to a destination B, e.g., acritical crossing of a part of the path where road work is beingperformed, etc.

However, it should again be determined that the prediction does not relyon actual orders or reservations for a future utilization of theresource. The concept of the current prediction method and system relieson interest regarding the resource and/or past utilization of theresource. This interest is measured in number of inquiries for theavailability of the resource at a given future point in time. Thus, thenumber of inquiries may be measured by the number of Internetconnections from a client browser to a server requesting informationabout the resource in question.

Moreover, the automatic inquiries described in the context of thenavigational system may also be performed in the context of any otherutilization prediction of any other resource, e.g., stock tradingvolumes, database usage, ferry passages, concert tickets, etc. (seeabove).

Embodiments of the invention may be implemented together with virtuallyany type of computer, regardless of the platform, being suitable forstoring and/or executing program code. For example, as shown in FIG. 4,a computing system 400 may include one or more processor(s) 402 with oneor more cores per processor, associated memory elements 404, an internalstorage device 406 (e.g., a hard disk, an optical drive, such as acompact disk drive or digital video disk (DVD) drive, a flash memorystick, a solid-state disk, etc.), and numerous other elements andfunctionalities, typical of today's computers (not shown). The memoryelements 404 may include a main memory, e.g., a random access memory(RAM), employed during actual execution of the program code, and a cachememory, which may provide temporary storage of at least some programcode and/or data in order to reduce the number of times, code and/ordata must be retrieved from a long-term storage medium or external bulkstorage 416 for an execution. Elements inside the computer 400 may belinked together by means of a bus system 418 with correspondingadapters. Additionally, the prediction system 204 may be attached to thebus system 418.

The computing system 400 may also include input means such as a keyboard408, a pointing device such as a mouse 410, or a microphone (not shown).Alternatively, the computing system may be equipped with a touchsensitive screen as a main input device. Furthermore, the computer 400,may include output means such as a monitor or screen 412 (e.g., a liquidcrystal display (LCD), a plasma display, a light emitting diode display(LED), or cathode ray tube (CRT) monitor). The computer system 400 maybe connected to a network (e.g., a local area network (LAN), a wide areanetwork (WAN)), such as the Internet or any other similar type ofnetwork, including wireless networks via a network interface connection414. This may allow a coupling to other computer systems, or a storagenetwork, or a tape drive. Those skilled in the art will appreciate thatmany different types of computer systems exist, and the aforementionedinput and output means may take other forms. Generally speaking, thecomputer system 400 may include at least the minimal processing, inputand/or output means, necessary to practice embodiments of the invention.

While the invention has been described with respect to a limited numberof embodiments, those skilled in the art, having benefit of thisdisclosure, will appreciate that other embodiments may be devised, whichdo not depart from the scope of the invention, as disclosed herein.Accordingly, the scope of the invention should be limited only by theclaims. Also, elements described in association with differentembodiments may be combined. It should also be noted that referencesigns in the claims, if any, should not be construed as limitingelements.

As will be appreciated by one skilled in the art, aspects of the presentdisclosure may be embodied as a system, method or computer programproduct. Accordingly, aspects of the present disclosure may take theform of an entirely hardware embodiment, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or anembodiment combining software and hardware aspects that may allgenerally be referred to herein as a “circuit,” “module” or “system.”Furthermore, aspects of the present disclosure may take the form of acomputer program product embodied in one or more computer readablemedium(s) having computer readable program code embodied thereon.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that may contain, or store, a programfor use, by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that may communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java, Smalltalk, C++, or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Aspects of the present disclosure are described with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of thepresent disclosure. It will be understood that each block of theflowchart illustrations and/or block diagrams, and combinations ofblocks in the flowchart illustrations and/or block diagrams, may beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which execute via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in a computerreadable medium that may direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions, whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus, or other devices to produce a computerimplemented process such that the instructions, which execute on thecomputer or other programmable apparatus, provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram, block, or blocks.

The block diagrams in the Figures illustrate the architecture,functionality, and operation of possible implementations of systems,methods and computer program products, according to various embodimentsof the present disclosure. In this regard, each block in the blockdiagrams may represent a module, segment, or portion of code, whichcomprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions, discussed hereinabove, mayoccur out of the disclosed order. For example, two functions taught insuccession may, in fact, be executed substantially concurrently, or thefunctions may sometimes be executed in the reverse order depending uponthe functionality involved. It will also be noted that each block of theblock diagrams, and combinations of blocks in the block diagrams, may beimplemented by special purpose hardware-based systems that perform thespecified functions or acts, or combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to limit the invention. As usedherein, the singular forms “a”, “an” and “the” are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. It will further be understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of anymeans or steps plus function elements in the claims below are intendedto include any structure, material, or act for performing the functionin combination with other claimed elements, as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Theembodiment was chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications, as are suited to theparticular use contemplated.

What is claimed is:
 1. A computer-implemented method comprising: predicting, by one or more processors, future utilization of a resource at a future point in time, the predicting comprising: receiving, by the one or more processors, inquiries on potential future utilization of the resource for different future points in time, wherein each inquiry comprising a portion of the inquiries is received over an Internet; recording, by the one or more processors, time-based patterns of the inquiries that are received to provide recorded time-based patterns of received inquiries; recording, by the one or more processors, an historic actual utilization value of the resource to provide a recorded historic actual utilization value; and determining, by the one or more processors, future utilization of the resource at a given future time using the recorded time-based patterns of received inquiries, the recorded historic actual utilization value of the resources, and a current inquiry pattern for the resource; and performing, by the one or more processors, an action on the resource in advance of the given time, based on the determined future utilization, wherein the action is selected from the group consisting of a maintenance action, a preventative customer service action, digesting workload throttling of a database system comprising the resource, and optimizing the resource for future usage.
 2. The method of claim 1, wherein said historic actual utilization value is recorded as an average utilization value during discrete predefined time periods.
 3. The method of claim 1, wherein the determining is based on a parameter reflecting an external influence factor of the historic actual utilization value.
 4. The method of claim 1, wherein the resource is a time dependent service.
 5. The method of claim 1, wherein the determined future utilization comprises a forecasted potential bottleneck.
 6. The method of claim 1, wherein the resource comprises a database resource of the database system, the action comprises the digesting the database system workload throttling, and the given time comprises prior to current database resource consumption reaching a predefined critical consumption level.
 7. The method of claim 1, wherein the resource comprises a computing resource in a shared multi-user computing environments and the action comprises the optimizing the resource for the future usage.
 8. The method of claim 1, wherein the resource comprises a database resource of a database system and the action comprises generating a consumption map of the resource. 